It is known that in a dynamic on-demand enterprise environment, such as an enterprise environment, enterprise performance management (EPM) is critical to enable a globally integrated enterprise (GIE) model with improved agility. Enterprise performance management facilitates the capture of core enterprise metrics, thereby enabling the detection of control action triggers. Traditionally, enterprise performance management and process automation are treated separately and implemented as individual silos. Such an approach results in a decreased ability of the enterprise to adapt to significant changes in a meaningful timeframe. When realizing EPM architectures, it is important to unambiguously define the data model and process model attributes associated with process automation. It is also critical to clearly define the interfaces between the performance management and process automation components, and the required and enabling artifacts.
While there are some traditional approaches for attempting to improve the communication language between process automation and enterprise performance management, they do not mitigate issues resulting from the segregated approach used in designing, modeling, architecting, and implementing process automation and performance management components. Another issue with traditional approaches is the challenges involved in dynamic addition of new enterprise components, or modifications of existing ones.